Fibroblast Subtypes Research Articles

Abstract 6213: Determination of permissive and restraining cancer-associated fibroblast (DeCAF) subtypes

Abstract Cancer-associated fibroblasts (CAFs) in pancreatic adenocarcinoma (PDAC) are known to play a significant role in regulating tumor progression, invasion, and metastasis. Multiple studies using experimental strategies, as well as single-cell RNA-sequencing (scRNAseq) technology, have shown the existence of subpopulations of PDAC CAFs, with divergent physical and biological characteristics. However, how these CAF subpopulations translate to clinical practice remains unclear. Using a combination of sc- and bulk RNAseq data, we present two CAF subtypes with permissive (permCAF) and restraining (restCAF) characteristics in patients, and developed a clinically usable single-sample classifier (DeCAF) using using 11 independent datasets with high reproducibility (AUC = 0.961). We found that the permCAF patients tend to be associated with a “myxoid” histological features, while restCAF samples were more “collagenized” (p = 0.018). Patients with permCAF tumors had a median overall survival (OS) of 18.5 m compared to 30.2 m for restCAF tumors, with a stratified HR = 1.66 (p < 0.001) for patients with permCAF tumors. Basal-like tumors were found to be associated permCAF subtype (p < 0.001). DeCAF and PurIST (basal-like/classical) subtypes were independently associated with OS (p < 0.001). Analysis of a phase Ib trial FOLFIRINOX in combination with a CCR2 inhibitor (PF-04136309; NCT01413022) , we found that in patients with classical tumors, increasing permCAF probability was associated with response (r = -0.688, p<0.001). Tumors with permCAF subtype are enriched in neutrophils using CIBERSORT and may explain the positive response to CCR2 inhibition. More intriguingly, we found similar associations with OS in kidney renal clear cell carcinoma (KIRC, p = 0.001) and mesothelioma (MESO, p = 0.019). DeCAF subtypes are associated with histological subtype in MESO (p = 0.021) and grade in KIRC (p = 0.056). Taken together, DeCAF subtypes explain the role of CAF subtypes in patients, provide a foundation for the translation of preclinical studies, and facilitate the design of future therapeutic approaches and clinical trials. Citation Format: Xianlu Laura Peng, Elena Kharitonova, Joseph Kearney, Yi Xu, Priscilla Chan, Changfei Luan, Brian Belt, Roheena Panni, Arthi Hariharan, Ian McCabe, Ashley Morrison, Ashley Cliff, David C. Linehan, Alina Iuga, Naim U. Rashid, Jen Jen Yeh. Determination of permissive and restraining cancer-associated fibroblast (DeCAF) subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6213.

Cancer-associated fibroblasts: protagonists of the tumor microenvironment in gastric cancer.

Enhanced knowledge of the interaction of cancer cells with their environment elucidated the critical role of tumor microenvironment in tumor progression and chemoresistance. Cancer-associated fibroblasts act as the protagonists of the tumor microenvironment, fostering the metastasis, stemness, and chemoresistance of cancer cells and attenuating the anti-cancer immune responses. Gastric cancer is one of the most aggressive cancers in the clinic, refractory to anti-cancer therapies. Growing evidence indicates that cancer-associated fibroblasts are the most prominent risk factors for a poor tumor immune microenvironment and dismal prognosis in gastric cancer. Therefore, targeting cancer-associated fibroblasts may be central to surpassing resistance to conventional chemotherapeutics, molecular-targeted agents, and immunotherapies, improving survival in gastric cancer. However, the heterogeneity in cancer-associated fibroblasts may complicate the development of cancer-associated fibroblast targeting approaches. Although single-cell sequencing studies started dissecting the heterogeneity of cancer-associated fibroblasts, the research community should still answer these questions: "What makes a cancer-associated fibroblast protumorigenic?"; "How do the intracellular signaling and the secretome of different cancer-associated fibroblast subpopulations differ from each other?"; and "Which cancer-associated fibroblast subtypes predominate specific cancer types?". Unveiling these questions can pave the way for discovering efficient cancer-associated fibroblast targeting strategies. Here, we review current knowledge and perspectives on these questions, focusing on how CAFs induce aggressiveness and therapy resistance in gastric cancer. We also review potential therapeutic approaches to prevent the development and activation of cancer-associated fibroblasts via inhibition of CAF inducers and CAF markers in cancer.

The role of dermal fibroblasts in autoimmune skin diseases.

Fibroblasts are an important subset of mesenchymal cells in maintaining skin homeostasis and resisting harmful stimuli. Meanwhile, fibroblasts modulate immune cell function by secreting cytokines, thereby implicating their involvement in various dermatological conditions such as psoriasis, vitiligo, and atopic dermatitis. Recently, variations in the subtypes of fibroblasts and their expression profiles have been identified in these prevalent autoimmune skin diseases, implying that fibroblasts may exhibit distinct functionalities across different diseases. In this review, from the perspective of their fundamental functions and remarkable heterogeneity, we have comprehensively collected evidence on the role of fibroblasts and their distinct subpopulations in psoriasis, vitiligo, atopic dermatitis, and scleroderma. Importantly, these findings hold promise for guiding future research directions and identifying novel therapeutic targets for treating these diseases.

Single-cell RNA-seq reveals keratinocyte and fibroblast heterogeneity and their crosstalk via epithelial-mesenchymal transition in psoriasis

The pathogenesis of psoriasis, a chronic inflammatory autoimmune skin disease with a high global prevalence, remains unclear. We performed a high-resolution single-cell RNA sequencing analysis of 94,759 cells from 13 samples, including those from psoriasis model mice and wild-type mice. We presented a single-cell atlas of the skin of imiquimod-induced mice with psoriasis and WT mice, especially the heterogeneity of keratinocytes and fibroblasts. More interestingly, we discovered that special keratinocyte subtypes and fibroblast subtypes could interact with each other through epithelial–mesenchymal transition and validated the results with drug verification. Moreover, we conducted a tentative exploration of the potential pathways involved and revealed that the IL-17 signalling pathway may be the most relevant pathway. Collectively, we revealed the full-cycle landscape of key cells associated with psoriasis and provided a more comprehensive understanding of the pathogenesis of psoriasis.

Single cell and bulk RNA sequencing identifies tumor microenvironment subtypes and chemoresistance-related IGF1+ cancer-associated fibroblast in gastric cancer

BackgroundThe tumor microenvironment (TME) significantly influences prognosis and drug resistance in various tumors, yet its heterogeneity and the mechanisms affecting therapeutic response remain unclear in gastric cancer (GC). MethodsThe heterogenous TME were explored with single-cell RNA-sequencing (scRNA-seq) data of 50 primary GC samples. We then identified four GC TME subtypes with nonnegative matrix factorization (NMF) and constructed a pearson nearest-centroid classifier based on subtype-specific upregulated genes. Genomic features and clinical significance of four subtypes were comprehensively evaluated. We reclustered fibroblasts to identify cancer-associated fibroblast (CAF) subtype associated with poor clinical outcomes. RT-qPCR and double immunofluorescence staining were applied to validate the findings. Cellchat analysis elucidated potential molecular mechanisms of the CAF subtype in GC disease progression and chemotherapy resistance. FindingsThe GC TME exhibited high heterogeneity, influencing chemo-sensitivity. Four TME-based subtypes predicting response to immunotherapy and chemotherapy were identified and validated in 1406 GC patients. Among which, ISG1 subtype displayed higher fibroblasts infiltration and heightened oncogenic pathways, and inferior response to chemotherapy with unfavorable prognosis. Microsatellite instability-high (MSI-H) GCs within four TME subtypes showed immunological heterogeneity. We then reported an IGF1-overexpressing CAF was associated with chemo-resistance and GC recurrence. Cell communication analysis revealed IGF1+ CAF may induce drug-resistant phenotypes in tumor cells through IGF1-α6β4 integrin ligand-receptor binding and activation of EMT biological process. InterpretationWe identified four TME-based subtypes with different clinical outcomes and IGF1+ CAFs contributing to poor clinical outcomes in GC, which might provide guidance for individualized treatment and facilitate the development of novel therapeutic targets.

A gene signature linked to fibroblast differentiation for prognostic prediction of mesothelioma

BackgroundMalignant mesothelioma is a type of infrequent tumor that is substantially related to asbestos exposure and has a terrible prognosis. We tried to produce a fibroblast differentiation-related gene set for creating a novel classification and prognostic prediction model of MESO.MethodThree databases, including NCBI-GEO, TCGA, and MET-500, separately provide single-cell RNA sequencing data, bulk RNA sequencing profiles of MESO, and RNA sequencing information on bone metastatic tumors. Dimensionality reduction and clustering analysis were leveraged to acquire fibroblast subtypes in the MESO microenvironment. The fibroblast differentiation-related genes (FDGs), which were associated with survival and subsequently utilized to generate the MESO categorization and prognostic prediction model, were selected in combination with pseudotime analysis and survival information from the TCGA database. Then, regulatory network was constructed for each MESO subtype, and candidate inhibitors were predicted. Clinical specimens were collected for further validation.ResultA total of six fibroblast subtypes, three differentiation states, and 39 FDGs were identified. Based on the expression level of FDGs, three MESO subtypes were distinguished in the fibroblast differentiation-based classification (FDBC). In the multivariate prognostic prediction model, the risk score that was dependent on the expression level of several important FDGs, was verified to be an independently effective prognostic factor and worked well in internal cohorts. Finally, we predicted 24 potential drugs for the treatment of MESO. Moreover, immunohistochemical staining and statistical analysis provided further validation.ConclusionFibroblast differentiation-related genes (FDGs), especially those in low-differentiation states, might participate in the proliferation and invasion of MESO. Hopefully, the raised clinical subtyping of MESO would provide references for clinical practitioners.

A specific inflammatory suppression fibroblast subpopulation characterized by MHCII expression in human dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is a significant cause of heart failure that requires heart transplantation. Fibroblasts play a central role in the fibro-inflammatory microenvironment of DCM. However, their cellular heterogeneity and interaction with immune cells have not been well identified. An integrative analysis was conducted on single-cell RNA sequencing (ScRNA-Seq) data from human left ventricle tissues, which comprised 4 hearts from healthy donors and 6 hearts with DCM. The specific antigen-presenting fibroblast (apFB) was explored as a subtype of fibroblasts characterized by expressing MHCII genes, the existence of which was confirmed by immunofluorescence staining of 3 cardiac tissues from DCM patients with severe heart failure. apFB highly expressed the genes that response to IFN-γ, and it also have a high activity of the JAK-STAT pathway and the transcription factor RFX5. In addition, the analysis of intercellular communication between apFBs and CD4+T cells revealed that the anti-inflammatory ligand-receptor pairs TGFB-TGFR, CLEC2B-KLRB1, and CD46-JAG1 were upregulated in DCM. The apFB signature exhibited a positive correlation with immunosuppression and demonstrated diagnostic and prognostic value when evaluated using a bulk RNA dataset comprising 166 donors and 166 DCM samples. In conclusion, the present study identified a novel subpopulation of fibroblasts that specifically expresses MHCII-encoding genes. This specific apFBs can suppress the inflammation occurring in DCM. Our findings further elucidate the composition of the fibro-inflammatory microenvironment in DCM, and provide a novel therapeutic target.

Single-cell sequencing reveals Hippo signaling as a driver of fibrosis in hidradenitis suppurativa.

Hidradenitis suppurativa (HS) is a chronic inflammatory disease characterized by abscesses, nodules, dissecting/draining tunnels, and extensive fibrosis. Here, we integrate single-cell RNA sequencing, spatial transcriptomics, and immunostaining to provide an unprecedented view of the pathogenesis of chronic HS, characterizing the main cellular players and defining their interactions. We found a striking layering of the chronic HS infiltrate and identified the contribution of 2 fibroblast subtypes (SFRP4+ and CXCL13+) in orchestrating this compartmentalized immune response. We further demonstrated the central role of the Hippo pathway in promoting extensive fibrosis in HS and provided preclinical evidence that the profibrotic fibroblast response in HS can be modulated through inhibition of this pathway. These data provide insights into key aspects of HS pathogenesis with broad therapeutic implications.

Myofibroblastic cancer-associated fibroblast subtype heterogeneity in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) has a fibrotic stroma that has both tumor-promoting and tumor-restraining properties. Different types of cancer-associated fibroblasts (CAFs) have been described. Here, we investigated whether CAFs within the same subtype exhibit heterogeneous functions. We evaluated the gene and protein expression differences in two myofibroblastic CAF (myCAF) lines using single-cell and bulk RNA-sequencing. We utilized proliferation and migration assays to determine the effect of different CAF lines on a tumor cell line. We found that myCAF lines express an activated stroma subtype gene signature, which is associated with a shorter survival in patients. Although both myCAF lines expressed α-smooth muscle actin (α-SMA), platelet-derived growth factor-α (PDGFR-α), fibroblast-activated protein (FAP), and vimentin, we observed heterogeneity between the two lines. Similarly, despite being consistent with myCAF gene expression overall, heterogeneity within specific genes was observed. We found that these differences extended to the functional level where the two myCAF lines had different effects on the same tumor cell line. The myCAF216 line, which had slightly increased inflammatory CAF-like gene expression and higher protein expression of α-SMA, PDGFR-α, and FAP was found to restrain migration of tumor cells. We found that two myCAF lines with globally similar expression characteristics had different effects on the same tumor cell line, one promoting and the other restraining migration. Our study highlights that there may be unappreciated heterogeneity within CAF subtypes. Further investigation and attention to specific genes or proteins that may drive this heterogeneity will be important.

Abstract A035: Stromal composition, fibroblast heterogeneity and spatial organization in pancreatic adenocarcinoma

Abstract Background: The pancreatic ductal adenocarcinoma (PDAC) microenvironment is characterized by highly abundant stromal fibroblasts that are hypothesized to influence tumor behavior. While recent studies have identified multiple populations of stromal fibroblasts with divergent roles in PDAC biology, stromal composition remains incompletely characterized in human tumors, including the landscape of fibroblast subtypes and their spatial organization. Design: We designed multiplex immunofluorescence assays to quantify tumor cells (cytokeratin), immune cells (CD45), fibroblasts (αSMA, CD74, FAP, LaminA), other cells (CD31, CD56, CALD1, NG2), and collagen I in fixed tissue sections. Combinatorial fibroblast marker expression identified myofibroblasts (myCAF), inflammatory fibroblasts (iCAF), antigen-presenting fibroblasts (apCAF), and other hybrid fibroblast subtypes. We characterized fibroblast populations in up-front resected and neoadjuvant-treated cohorts of patients with localized PDAC and in patients with biopsies of metastatic lesions. Using digital imaging, supervised machine learning, and spatial proximity metrics, we quantified cell phenotypes, fibroblast subtype composition and spatial organization at the single-cell level and in the context of tumor clinicopathologic features and patient outcomes. Results: Across 301 up-front resected tumors, we cumulatively analyzed 1.7 million cells, including 611,000 fibroblasts. Stromal fibroblast density ranged from 632 to 4150 cells/mm2. Five main fibroblast subtypes constituted more than 85% of the fibroblast population in these tumors: αSMA+ (myCAF), FAP+αSMA+ (FAP+ myCAF), LaminA+ (iCAF), αSMA+ LaminA+ (myCAF/iCAF), and FAP+ αSMA+ LaminA+ (FAP+ myCAF/iCAF). Unexpectedly, 39% of fibroblasts showed co-expression of markers previously considered distinct for major fibroblast subtypes. By unsupervised clustering of fibroblast subtype proportions, we identified 3 fibroblast-defined tumor subgroups, including tumors rich in FAP+ fibroblasts, hybrid fibroblasts, and single positive fibroblasts (myCAFs, iCAFs, and apCAFs), which were associated with patient survival. Furthermore, fibroblast subtypes were spatially organized, with preferential localization of FAP+ myCAFs near tumor cells and iCAFs more distant from tumor cells yet closer to immune cells. FAP+ myCAFs were more abundant in basal-like tumors than in classical tumors, and FAP+ myCAFs were located closer to basal-like tumor cells than classical tumor cells within individual tumors. Compared to up-front resected primary tumors, neoadjuvant FOLFIRINOX treated tumors and metastatic lesions harbored distinct fibroblast profiles. Conclusion: Fibroblasts in the PDAC microenvironment are heterogeneous both in abundance and subtype composition, exhibit distinct spatial organization and are associated with patient outcomes. Treatment with FOLFIRINOX alters the composition of fibroblast subtypes in primary PDAC, and metastatic PDAC lesions have a different fibroblast composition compared to primary tumors. Citation Format: Dalia Elganainy, Andressa Dias Costa, Alexander Jordan, Suryun Kim, Sara A. Väyrynen, Hannah L. Williams, Chen Yuan, Douglas A. Rubinson, Kimberly Perez, Harshabad Singh, Richard F. Dunne, Thomas E. Clancy, David C. Linehan, Daniel T. Chang, Aram F. Hezel, Albert C. Koong, Andrew Aguirre, Brian M. Wolpin, Jonathan A. Nowak. Stromal composition, fibroblast heterogeneity and spatial organization in pancreatic adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr A035.

Abstract B107: Spatial transcriptomics analysis of PanIN reveals loss of pro-inflammatory signaling and the presence of cancer-associated fibroblasts

Abstract Pancreatic intraepithelial neoplasia (PanIN) is a premalignant lesion that potentially progresses into pancreatic ductal adenocarcinoma (PDAC). Since PanIN diagnosis is restricted to formalin-fixed and paraffin-embedded (FFPE) samples, little is known about PanIN interactions with the surrounding microenvironment due to the technical limitations to perform genome-wide single-cell analysis. We developed whole transcriptome spatial technology for FFPE to provide the ideal tool to profile PanINs in their microenvironment. We performed FFPE spatial transcriptomics (ST) using the Visium (10x Genomics) approach in a cohort of 14 PanIN lesions (9 low-grade and 5 high-grade). To overcome experimental limitations, we developed an artificial intelligence method to integrate imaging, spatial transcriptomics, and single-cell RNA-seq (scRNA-seq) analyses. Imaging analysis of the same stained sections used for ST was applied before gene expression exploration. Using machine learning to annotate cell types, we were able to deconvolve and quantify the cell types per ST spot using cell morphology instead of a scRNA-seq gene expression reference. Subsequently, we applied transfer learning to a scRNA-seq PDAC atlas that was built from multiple published datasets. The whole transcriptome ST findings were confirmed using targeted single-cell transcriptomics (Xenium, 10x Genomics) and proteomics (imaging mass cytometry, IMC). The analysis revealed that PanINs already exhibit molecular and cellular features of PDAC, including expression of the PDAC classical subtype signature and the presence of the same cancer-associated fibroblast (CAF) subtypes enriched in invasive carcinoma stages. The CAF subtypes, including the recently described antigen-presenting CAFs, were confirmed at single-cell resolution using Xenium and IMC. Integrating multi-omics data with a PDAC scRNA-seq atlas through transfer learning, revealed that an inflammatory pattern gradually decreases during PanIN progression, accompanied by a compensatory increase in proliferation pathways in the PanIN cells relative to normal duct cells. This trend between inflammation and proliferation was confirmed specifically in PanIN cells using Xenium. Our experimental and computational approach provides valuable insights into the dynamics of pancreatic tumor progression from PanIN lesions using innovative methods to provide a unique spatial multi-omics reference of PanINs. Citation Format: Alexander T.F. Bell, Jacob T. Mitchell, Ashley L. Kiemen, Melissa Lyman, Kohei Fujikura, Jae W. Lee, Erin Coyne, Sarah M. Shin, Pei-Hsun Wu, Jacquelyn W. Zimmerman, Denis Wirtz, Won J. Ho, Neeha Zaidi, Elizabeth Thompson, Elizabeth M. Jaffee, Laura D. Wood, Elana J. Fertig, Luciane T. Kagohara. Spatial transcriptomics analysis of PanIN reveals loss of pro-inflammatory signaling and the presence of cancer-associated fibroblasts [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B107.

Abstract C015: Clinically usable classification of cancer-associated fibroblast subtypes in pancreatic cancer

Abstract Background: Cancer-associated fibroblasts (CAFs) in pancreatic adenocarcinoma (PDAC) are known to play a significant role in regulating tumor progression, invasion, and metastasis. Multiple studies using experimental strategies, as well as single-cell RNA-sequencing (scRNAseq) technology, have shown the existence of subpopulations of PDAC CAF cells, with divergent physical and biological characteristics. However, how to translate CAF cell subpopulations to the clinic remains unclear. Methods: We developed a computational method for scRNAseq, SCISSORS, to identify rare cell clusters and determine exemplar genes. Using SCISSORS, we have defined human exemplar genes of the previously described myCAF and iCAF cell subpopulations using scRNAseq data. These exemplar genes were then used to develop a single-sample classifier (SSC) for PDAC CAFs that we call CAPER in bulk RNAseq data. CAPER was trained using penalized logistic regression in 4 datasets (n= 372) and validated in 8 datasets (n= 593). Results: SCISSORS was able to identify rare cells such as previously described apCAFs (0.59% of cells) and basal-like cell clusters (0.092% of cells) that were missed in the previous analysis. We hypothesized that the sensitivity of SCISSORS would allow us to define exemplar genes that may be applied to bulkRNAseq. Indeed, the top ranked 25 exemplar genes defined by SCISSORS were associated with overall survival (OS) (10 datasets, n=948, p=0.017, log-rank test). To develop a clinically usable classifier, we used the SCISSORS exemplar genes to develop the SSC CAPER which consists of 9 gene pairs. CAPER CAF calls in the validation datasets showed high reproducibility compared with cluster-based labels (AUC: 0.956). In a meta-analysis, patients with CAPER myCAF subtypes showed shorter OS (median OS: 18.0m) compared to CAPER iCAF subtypes (median OS: 28.7m) (p<0.001, log-rank test). Multivariable analysis found that CAPER CAF subtypes were independently prognostic when included with PurIST tumor subtype calls (CAPER p<0.001, PurIST p<0.001, Cox regression). Interestingly, patients subtyped as basal-like for the tumor and myCAF for the CAF showed the worst outcome with a median OS of 11.2 months; while patients subtyped as classical for the tumor and iCAF for the CAF showed the best outcome with a median OS of 30.2 months (p<0.001, log-rank test). Conclusions: CAF genes have largely been evaluated in scRNAseq. We have defined CAF exemplar genes that can be applied to bulk RNAseq, and have developed a clinically usable classifier similar to the now CLIA-approved PurIST that we call CAPER that is robust and accurate for the classification of CAF subtypes in patients. The ability to evaluate CAF subtypes in bulk gene expression provides a powerful tool that may be applied to the plethora of data from patients and clinical trials. CAF subtypes are independently prognostic compared to tumor-intrinsic subtypes, supporting important biological implications, and may facilitate the design of future clinical trials. Citation Format: Xianlu L. Peng, Elena Kharitonova, Joseph Kearney, Ian McCabe, Madison Jenner, Ashley B. Morrison, Alina Iuga, Naim U. Rashid, Jen Jen Yeh. Clinically usable classification of cancer-associated fibroblast subtypes in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C015.

Evidence of steady-state fibroblast subtypes in the normal human breast as cells-of-origin for perturbed-state fibroblasts in breast cancer

BackgroundHuman breast cancer most frequently originates within a well-defined anatomical structure referred to as the terminal duct lobular unit (TDLU). This structure is endowed with its very own lobular fibroblasts representing one out of two steady-state fibroblast subtypes—the other being interlobular fibroblasts. While cancer-associated fibroblasts (CAFs) are increasingly appreciated as covering a spectrum of perturbed states, we lack a coherent understanding of their relationship—if any—with the steady-state fibroblast subtypes. To address this, we here established two autologous CAF lines representing inflammatory CAFs (iCAFs) and myofibroblast CAFs (myCAFs) and compared them with already established interlobular- and lobular fibroblasts with respect to their origin and impact on tumor formation.MethodsPrimary breast tumor-derived CAFs were transduced to express human telomerase reverse transcriptase (hTERT) and sorted into CD105low and CD105high populations using fluorescence-activated cell sorting (FACS). The two populations were tested for differentiation similarities to iCAF and myCAF states through transcriptome-wide RNA-Sequencing (RNA-Seq) including comparison to an available iCAF-myCAF cell state atlas. Inference of origin in interlobular and lobular fibroblasts relied on RNA-Seq profiles, immunocytochemistry and growth characteristics. Osteogenic differentiation and bone formation assays in culture and in vivo were employed to gauge for origin in bone marrow-derived mesenchymal stem cells (bMSCs). Functional characteristics were assessed with respect to contractility in culture and interaction with tumor cells in mouse xenografts. The cells’ gene expression signatures were tested for association with clinical outcome of breast cancer patients using survival data from The Cancer Genome Atlas database.ResultsWe demonstrate that iCAFs have properties in common with interlobular fibroblasts while myCAFs and lobular fibroblasts are related. None of the CAFs qualify as bMSCs as revealed by lack of critical performance in bone formation assays. Functionally, myCAFs and lobular fibroblasts are almost equally tumor promoting as opposed to iCAFs and interlobular fibroblasts. A myCAF gene signature is found to associate with poor breast cancer-specific survival.ConclusionsWe propose that iCAFs and myCAFs originate in interlobular and lobular fibroblasts, respectively, and more importantly, that the tumor-promoting properties of lobular fibroblasts render the TDLU an epicenter for breast cancer evolution.

Single-cell transcriptomic analysis of human pleura reveals stromal heterogeneity and informs in vitro models of mesothelioma.

The pleural lining of the thorax regulates local immunity, inflammation and repair. A variety of conditions, both benign and malignant, including pleural mesothelioma, can affect this tissue. A lack of knowledge concerning the mesothelial and stromal cells comprising the pleura has hampered the development of targeted therapies. Here, we present the first comprehensive single-cell transcriptomic atlas of the human parietal pleura and demonstrate its utility in elucidating pleural biology. We confirm the presence of known universal fibroblasts and describe novel, potentially pleural-specific, fibroblast subtypes. We also present transcriptomic characterisation of multiple in vitro models of benign and malignant mesothelial cells, and characterise these through comparison with in vivo transcriptomic data. While bulk pleural transcriptomes have been reported previously, this is the first study to provide resolution at the single-cell level. We expect our pleural cell atlas will prove invaluable to those studying pleural biology and disease. It has already enabled us to shed light on the transdifferentiation of mesothelial cells, allowing us to develop a simple method for prolonging mesothelial cell differentiation in vitro.

Identification of CGNL1 as a diagnostic marker in fibroblasts of diabetic foot ulcers: Insights from single cell RNA sequencing and bulk sequencing data.

This study aimed to explore the unique transcriptional feature of fibroblasts subtypes and the role of ferroptosis in diabetic foot ulcers (DFUs). The GEO (Gene Expression Omnibus) was searched to obtain the DFUs single-cell and transcriptional datasets. After identifying cell types by classic marker genes, the integrated single-cell dataset was used to run trajectory inference, RNA velocity, and ligand-receptor interaction analysis. Next, bulk RNA-seq datasets of DFUs were analyzed to the key ferroptosis genes. Here, we profile 83529 single transcriptomes from the foot samples utilizing single-cell sequencing (scRNA-seq) data of DFU from GEO database and identified 12 cell types, with fibroblasts exhibiting elevated levels of ferroptosis activity and substantial cellular heterogeneity. Our results defined six main fibroblast subsets that showed mesenchymal, secretory-reticular, secretory-papillary, pro-inflammatory, myogenesis, and healing-enriched functional annotations. Trajectory inference and cell-cell communication analysis revealed two major cell fates with subpopulations of fibroblasts and altered ligand-receptor interactions. Bulk RNA sequencing data identified CGNL1 as a distinctive diagnostic signature in fibroblasts. Notably, CGNL1 positively correlated with pro-inflammatory fibroblasts. Overall, our analysis delineated the heterogeneity present in cell populations of DFUs, showing distinct fibroblast subtypes characterized by their own unique transcriptional features and enrichment functions. Our study will help us better understand DFUs pathogenesis and identifies CGNL1 as a potential target for DFUs therapies.

Transcriptional profiling sheds light on the fibrotic aspects of idiopathic subglottic tracheal stenosis.

Idiopathic subglottic stenosis (ISGS) is a rare fibrotic disease of the upper trachea with an unknown pathomechanism. It typically affects adult Caucasian female patients, leading to severe airway constrictions caused by progressive scar formation and inflammation with clinical symptoms of dyspnoea, stridor and potential changes to the voice. Endoscopic treatment frequently leads to recurrence, whereas surgical resection and reconstruction provides excellent long-term functional outcome. This study aimed to identify so far unrecognized pathologic aspects of ISGS using single cell RNA sequencing. Our scRNAseq analysis uncovered the cellular composition of the subglottic scar tissue, including the presence of a pathologic, profibrotic fibroblast subtype and the presence of Schwann cells in a profibrotic state. In addition, a pathology-associated increase of plasma cells was identified. Using extended bioinformatics analyses, we decoded pathology-associated changes of factors of the extracellular matrix. Our data identified ongoing fibrotic processes in ISGS and provide novel insights on the contribution of fibroblasts, Schwann cells and plasma cells to the pathogenesis of ISGS. This knowledge could impact the development of novel approaches for diagnosis and therapy of ISGS.

Machine Learning and Single-Cell Analysis Identify Molecular Features of IPF-Associated Fibroblast Subtypes and Their Implications on IPF Prognosis.

Idiopathic pulmonary fibrosis (IPF) is a devastating lung disease of unknown cause, and the involvement of fibroblasts in its pathogenesis is well recognized. However, a comprehensive understanding of fibroblasts' heterogeneity, their molecular characteristics, and their clinical relevance in IPF is lacking. In this study, we aimed to systematically classify fibroblast populations, uncover the molecular and biological features of fibroblast subtypes in fibrotic lung tissue, and establish an IPF-associated, fibroblast-related predictive model for IPF. Herein, a meticulous analysis of scRNA-seq data obtained from lung tissues of both normal and IPF patients was conducted to identify fibroblast subpopulations in fibrotic lung tissues. In addition, hdWGCNA was utilized to identify co-expressed gene modules associated with IPF-related fibroblasts. Furthermore, we explored the prognostic utility of signature genes for these IPF-related fibroblast subtypes using a machine learning-based approach. Two predominant fibroblast subpopulations, termed IPF-related fibroblasts, were identified in fibrotic lung tissues. Additionally, we identified co-expressed gene modules that are closely associated with IPF-fibroblasts by utilizing hdWGCNA. We identified gene signatures that hold promise as prognostic markers in IPF. Moreover, we constructed a predictive model specifically focused on IPF-fibroblasts which can be utilized to assess disease prognosis in IPF patients. These findings have the potential to improve disease prediction and facilitate targeted interventions for patients with IPF.

Smoother: a unified and modular framework for incorporating structural dependency in spatial omics data

Spatial omics technologies can help identify spatially organized biological processes, but existing computational approaches often overlook structural dependencies in the data. Here, we introduce Smoother, a unified framework that integrates positional information into non-spatial models via modular priors and losses. In simulated and real datasets, Smoother enables accurate data imputation, cell-type deconvolution, and dimensionality reduction with remarkable efficiency. In colorectal cancer, Smoother-guided deconvolution reveals plasma cell and fibroblast subtype localizations linked to tumor microenvironment restructuring. Additionally, joint modeling of spatial and single-cell human prostate data with Smoother allows for spatial mapping of reference populations with significantly reduced ambiguity.

Epigenetic and Metabolic Reprogramming of Fibroblasts in Crohn's Disease Strictures Reveals Histone Deacetylases as Therapeutic Targets.

No effective therapeutic intervention exists for intestinal fibrosis in Crohn's disease [CD]. We characterized fibroblast subtypes, epigenetic and metabolic changes, and signalling pathways in CD fibrosis to inform future therapeutic strategies. We undertook immunohistochemistry, metabolic, signalling pathway and epigenetic [Transposase-Accessible Chromatin using sequencing] analyses associated with collagen production in CCD-18Co intestinal fibroblasts and primary fibroblasts isolated from stricturing [SCD] and non-stricturing [NSCD] CD small intestine. SCD/NSCD fibroblasts were cultured with TGFβ and valproic acid [VPA]. Stricturing CD was characterized by distinct histone deacetylase [HDAC] expression profiles, particularly HDAC1, HDAC2, and HDAC7. As a proxy for HDAC activity, reduced numbers of H3K27ac+ cells were found in SCD compared to NSCD sections. Primary fibroblasts had increased extracellular lactate [increased glycolytic activity] and intracellular hydroxyproline [increased collagen production] in SCD compared to NSCD cultures. The metabolic effect of TGFβ stimulation was reversed by the HDAC inhibitor VPA. SCD fibroblasts appeared 'metabolically primed' and responded more strongly to both TGFβ and VPA. Treatment with VPA revealed TGFβ-dependent and TGFβ-independent Collagen-I production in CCD-18Co cells and primary fibroblasts. VPA altered the epigenetic landscape with reduced chromatin accessibility at the COL1A1 and COL1A2 promoters. Increased HDAC expression profiles, H3K27ac hypoacetylation, a significant glycolytic phenotype and metabolic priming characterize SCD-derived as compared to NSCD fibroblasts. Our results reveal a novel epigenetic component to Collagen-I regulation and TGFβ-mediated CD fibrosis. HDAC inhibitor therapy may 'reset' the epigenetic changes associated with fibrosis.

Elucidating Cell Diversity and Functions of Human Brain Borders in Alzheimer’s Disease

AbstractBackgroundEmerging evidence shows that the brain border regions act as a functional neuro‐immune interface to conduct essential immune surveillance and immune defense1. The dysfunction of border immunity contributes to aging, microglial inflammatory response, and neurodegeneration2‐3.MethodWe conducted single nuclei multiome to simultaneously profile gene expression and open chromatin of dissected postmortem human brain borders from aged individuals with and without Alzheimer’s Disease (AD) (n = 32). We further generated border cell models from iPSCs and postmortem leptomeningeal cells to understand the effects of genetic and environmental factors on border cells.ResultWe detect diverse cell types at the brain borders, including unique endothelial, mural, immune, and fibroblast subtypes. Border‐associated macrophages (BAMs) display differential gene expressions from microglia and express AD risk genes, as nominated by genome‐wide association studies (GWAS). We discover cell‐type‐specific differentially expressed genes in AD individuals, particularly fibroblasts and BAMs. We identify gene regulatory networks and master regulators of specific border cell states. Human cell models of leptomeningeal cells display the signature of ex vivo AD fibroblasts upon amyloid‐β treatment, and iPSC‐derived choroid plexus models carrying the APOE4 risk alleles demonstrate differentially expressed genes related to immune and fibrotic response. Lastly, we explore ligand‐receptor interactions within the border niche and observe increased intercellular activities and altered communication patterns at AD brain borders.ConclusionOur study establishes a molecular map of human border cell types and reveals the functional effects of AD risk factors on brain border cells, providing significant insight into the border immune and fibrotic responses in AD pathogenesis.